Umeå University, Medicinska fakulteten

Umeå University is one of Sweden’s largest higher education institutions with over 37,000 students and about 4,700 employees. The University offers a diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry, was made here. At Umeå University, everything is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture.

The ongoing societal transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here.

Are you interested in learning more? Read about Umeå university as a workplace

The Faculty of Medicine, which consists of 13 departments, is responsible for biomedical research and courses in the field of nursing and health care and has an extensive research and graduate education in more than 80 subjects.

Together with SciLifeLab and in collaboration with the Wallenberg Centre for Molecular Medicine (WCMM), the university’s Faculties of Medicine and Science and Technology announce the appointment of an assistant professor. This appointment offers a unique opportunity to establish oneself as a researcher in the field of data-driven life science and includes access to a formidable package of resources.

Project description: DDLS Fellows Program

The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a 12-year initiative funded with a total of 3,1 billion SEK from the Knut and Alice Wallenberg Foundation. The purpose of the program is to recruit and train the next generation of researchers in data-driven life science and to create data-driven life scientists and to create globally leading computational and data science capabilities in life science in Sweden.

The program will recruit 39 eminent young group leaders as DDLS Fellows, launch over 210 postdoctoral positions and establish a research school for 260 PhDs, within both academia and industry. The program is coordinated by SciLifeLab, a nationwide research infrastructure and a hub for cross-disciplinary life sciences. The Fellows will be recruited to the 11 participating host universities/organizations, enabling them to link up with strong local research environments as well as with the national DDLS program. The DDLS program promotes collaborative interdisciplinary work and engagement with industry, healthcare and other national and international partners, such as WASP, with the aim of bridging the life science and data science communities.

The DDLS program will focus on four strategic areas of data-driven research: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and infection biology. We are now looking for the first 20 young group leaders to join us as DDLS Fellows.

Each DDLS Fellow will receive a recruitment package of 17 MSEK, which is meant to cover 5 years of his/her own salary, two PhD students and two postdoc positions, as well as running costs. The Fellow positions are tenure-track, and the universities/organizations will assume the long-term responsibility of their support as tenured faculty.

The future of life science is data-driven. Will you be leading that change with us? Then apply now!

Subject description and duties

Umeå University is seeking a DDLS Fellow in Data-driven Precision Medicine and Diagnostics

The subject area concerns research that will make use of computational tools to integrate molecular and clinical data for precision medicine and diagnostic development. The focus is on data integration, analysis, visualization, and data interpretation for patient stratification, discovery of biomarkers for disease risks, diagnosis, drug response and monitoring of health. The precision medicine research is expected to contribute with strong capabilities in machine learning and AI and other computational tools to make use of existing strong assets in Sweden, such as molecular data (e.g., omics), imaging, electronic health care records, longitudinal patient and population registries, biobanks and digital monitoring data.

The purpose of an appointment as an assistant professor is to provide you with every opportunity to conduct successful research within the above-described field, to develop as an autonomous researcher and research leader and to acquire further scientific and teaching qualifications in the discipline of data-driven precision medicine and diagnostics in order to meet the requirements for appointment as an associate professor. The position will mainly (at least 80%) be focused on obtaining scientific qualifications, with the remaining time largely devoted to obtaining teaching qualifications. Administrative tasks may also be included.


Eligible to apply for this appointment as an assistant professor is a person who has completed a PhD or has the corresponding research expertise. Primary consideration should be given to a person who has completed a PhD or achieved the equivalent expertise within five years of the deadline for application for employment as an assistant professor. However, a person who has completed a PhD or achieved the equivalent expertise at an earlier date may also be considered if there are exceptional circumstances. Exceptional circumstances are sick leave, parental leave or other similar circumstances (Chapter 4 Section 4a of the Swedish Higher Education Ordinance).

Assessment criteria

In assessing suitability for this appointment, primary consideration shall be given to research expertise. In addition, pedagogical skills and administrative skills will also be taken into account.

General assessment criteria for teaching staff at Umeå University are that the applicant has both a good ability to collaborate and the requisite competence and suitability in general to perform the duties of the post to a high standard.

Description of the assessment criteria

In assessing research expertise, specific consideration shall be given to the originality and autonomy of research and the potential for the applicant to develop their own successful line of research within data-driven precision medicine and diagnostics, in particular regarding the use of computational tools to integrate molecular and clinical data for precision medicine and diagnostic development. Ability to integrate, analyze, visualize and interpret data for patient stratification, discovery of diagnostic biomarkers for disease risk, drug response and monitoring of health will be assessed. Furthermore, the assessment includes the applicant's potential to contribute to building competence in machine learning, AI and other computational tools, as well as making use of existing strong assets in Sweden, such as molecular data (e.g., omics), imaging, electronic health care records, longitudinal patient and population registries, biobanks and digital monitoring data.

Postdoctoral research conducted outside the university at which the applicant completed their PhD provides a particularly useful qualification.

In assessing teaching expertise, consideration will be given to the planning, implementation and evaluation of teaching, as well as to academic supervision and examinations.

Administrative skills can be demonstrated through experience of planning first and second-cycle courses and programmes, the ability to lead and help other to develop, etc. 

For this appointment, a particularly useful qualification is provided by experience of research in the field of data-driven life science, especially specialization in precision medicine and diagnostics, including the use of computational tools to integrate molecular and clinical data for precision medicine and diagnostic development, and the applicant is expected to have a research profile that fits the purpose of the appointment.

More about the appointment

Organisationally, the position in question will be affiliated to either the Faculty of Medicine or Faculty of Science and Technology. Departmental affiliation will be decided in consultation with the successful candidate, based on where their research best fits. Please feel free to state your preferred department in your application.
Link to website with information on potential host departments, WCMM and available infrastructure.

The position is a five-year, full-time, fixed-term appointment pursuant to Chapter 4 Section 12a of the Higher Education Ordinance, with the right to be considered for promotion to associate professor. The criteria for promotion shall be determined no later than the start of employment. An application to be considered for promotion must be submitted six months before the end of the fixed-term appointment. If, after due consideration, it is decided not to promote an assistant professor, the fixed-term appointment shall be terminated.

A teaching and research development plan shall be drawn up in conjunction with the appointment and one teaching and two research mentors shall be appointed to support the successful candidate in implementing this plan.

Last application date is 2022-07-27. Instructions for the application and a list of the documents to be attached to the application can be found here.

You apply via our e-recruitment system which you can reach via the application button below. When the application is received, you will receive a confirmation email.

We welcome your application!

Type of employment Temporary position
Contract type Full time
First day of employment According to agreements
Salary Monthly salary
Number of positions 1
Full-time equivalent 100 %
City Umeå
County Västerbottens län
Country Sweden
Reference number AN 2.2.1-845-22
  • Lars Nyberg , 070-6092775
Union representative
  • SACO, +4690-7865365
  • SEKO, +4690-7865296
  • ST, +4690-7865431
Published 17.May.2022
Last application date 27.Jul.2022 11:59 PM CEST

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